The performance evaluation of Web applications usually requires the analysis of sequences of user requests for specific Web pages. These sequences can be obtained, for example, by applying empirical methods (recording the real sequence of requests), or by applying a formal model for generating synthetic results. In this paper, we present our Web Browsing Model and and its implementation as part of our novel User Centric Walk algorithm. By taking into account the hyperlink structure as well as the different user behavior on the Web, User Centric Walk allows us to generate accurate synthetic data that can be used instead of empirically obtained requests. Additionally, in this paper we show using empirical data that the probability of choosing some hyperlink from a given page as well as the probability of a user leaving a page without following a hyperlink is best characterized by a power-law. Finally, we show the flexibility and applicability of our model by performing the required correlations to empirical data, in order to validate our approach.